Preventative management of water supplies is not only useful in keeping society safe and prosperous but also critical in avoiding the cost of potentially expensive reactive measures that may be necessary to resolve contamination. There is a wide variety of potential sources for contamination of such water supplies, including naturally-occurring phenomena as well as human-induced events. History demonstrates the pervasiveness of such threats and the future beckons for an accurate and reliable apparatus and method for detecting and predicting whether such water supplies are and will be contaminated.
Water quality events which may contaminate the water supply include a variety of chemical and biological processes and agents. Examples of such water quality events include nitrification, algae bloom, and deliberately sabotaging a water supply with bacteria like Escherichia coli. The example of nitrification is one that demonstrates how the detection and prediction of such an event can avert a potentially threatening and costly situation. Nitrification is a microbial process by which reduced nitrogen compounds, primarily ammonia, are sequentially oxidized to nitrite and nitrate by ammonia oxidizing bacteria and nitrite oxidizing bacteria, respectively. Nitrification must be avoided or controlled because of its potential effect on disinfectant residuals, which must be maintained at regulatory levels to ensure water safety. Nitrification can become a pervasive, persistent problem if allowed to develop, creating chronic disinfection residual challenges and the potential for unsafe water in the distribution system. The appearance of nitrate, via the formation of nitrite, in addition to the decrease of ammonia and total chlorine in the water, are the commonly known indicators that nitrification is occurring. In fact, there may be a number of other indicators among measurable water quality parameters that may signify the presence or impending onset of nitrification.
The fact that the relationships of these water quality parameters to particular water quality events are not readily understood or defined, coupled with the reality that the data for such parameters are often dynamic, noisy, and non-linear in fashion, contributes to the lack of a proactive system to accurately and reliably forecast water quality conditions. Instead, current monitoring systems employ passive methods to observe and manage water supplies. There exists a need for a flexible system with the capability to provide on-line, real-time evaluation of these water quality parameters in order to not only detect but also predict potentially harmful water quality events. The expression “real-time”, as used herein, refers to simultaneous as well as slightly delayed (i.e., substantially real-time or delayed by a relatively short period of time, e.g., not more than one second, not more than one minute, not more than one hour, or not more than one day). With such a system, water quality control officials will have more options with which to deal with threatening water quality events and will be able to utilize preventative and proactive management strategies to minimize the costly impact of such threats.